The Baseline That Broke the Hypothesis: How a Microbenchmark Proved SmallVec Was the Culprit

In the disciplined practice of performance engineering, few moments are as decisive as the one captured in message 1025 of this opencode session. After weeks of architectural work across Phases 0 through 3 of the cuzk project—building a pipelined Groth16 proving engine for Filecoin's Proof-of-Replication (PoRep), implementing cross-sector batching, and achieving a solid baseline of 88.9 seconds for a single 32 GiB proof—the team had entered Phase 4: compute-level optimizations. Five changes were implemented in Wave 1: A1 (SmallVec for the LC Indexer), A2 (pre-sizing vectors), A4 (parallelizing B_G2 CPU MSMs), B1 (pinning host memory with cudaHostRegister), and D4 (per-MSM window tuning). But when all five were applied together, the proof time regressed to 106 seconds—a 17-second slowdown.

The diagnosis that followed was a masterclass in systematic performance debugging. First, the CUDA timing instrumentation (CUZK_TIMING printf's) revealed that B1's memory pinning added 5.7 seconds of overhead, far exceeding the estimated 150–300 milliseconds. Reverting B1 brought the total down to 94.4 seconds, but this was still 5.5 seconds above baseline, with synthesis alone taking 60.3 seconds versus an expected ~54 seconds. The remaining suspect was A1: replacing Vec<(usize, Scalar)> with SmallVec<[(usize, Scalar); 4]> in the LC Indexer, an optimization that was supposed to reduce heap allocations and improve performance.

Message 1025 is the moment this hypothesis was tested—and shattered.

The Message: Running the Vec Baseline

The message itself is deceptively simple. It contains a single bash command that runs the synth-only microbenchmark with the original Vec implementation, measuring synthesis time across three iterations:

[assistant] [bash] echo "=== Vec (original baseline) ==="
FIL_PROOFS_PARAMETER_CACHE=/data/zk/params /home/theuser/curio/extern/cuzk/target/release/cuzk-bench synth-only --c1 /data/32gbench/c1.json --iterations 3 2>&1
=== Vec (original baseline) ===
=== Synthesis Microbenchmark ===
c1:         /data/32gbench/c1.json
sector:     1 (miner 1000)
partition:  all
iterations: 3

c1 loaded:  51510727 bytes
[2026-02-17T23:13:36.015050Z  INFO synthesize_porep_c2_batch{job_id="synth-bench-0"}: 
  cuzk_core::pipeline: building circuits for all partitions (parallel) num_partitions=10
[2026-02-17T23:13:36.022110Z  INFO ...

The output is truncated in the conversation data, but the result is clear from the surrounding context: Vec completes synthesis in 54.5 seconds, compared to the SmallVec cap=1 result of 59.5–59.9 seconds measured just minutes earlier in message 1021. This is a definitive 5–6 second regression caused by the SmallVec optimization—a finding that directly contradicted the original optimization proposal's assumptions.

The Reasoning and Motivation Behind the Message

To understand why message 1025 was written, one must trace the chain of reasoning that led to this precise moment. The assistant had already invested significant effort in building the synth-only microbenchmark (messages 1000–1019), recognizing that the full daemon-based E2E test was too slow for iterative A/B testing. Each full proof run required loading SRS parameters from disk, initializing GPU state, and waiting for GPU proving—adding minutes of overhead that made rapid iteration impossible.

The microbenchmark was a strategic investment: by linking cuzk-core directly into cuzk-bench under a new synth-bench feature, the assistant could call synthesize_porep_c2_batch() directly, bypassing the daemon, the GPU, and SRS loading entirely. This reduced each test iteration from several minutes to under a minute, enabling the systematic comparison of four configurations: Vec (original), SmallVec cap=1, cap=2, and cap=4.

Message 1021 had already tested SmallVec cap=1, yielding 59.5–59.9 seconds. Message 1025 was the control experiment: revert to Vec and measure the baseline. The assistant's reasoning, visible in the preceding messages, was that cap=1 should be the optimal SmallVec configuration—it minimizes inline storage (40 bytes per entry, fitting in a single 64-byte cache line) while still eliminating heap allocations for the majority of linear combinations that have exactly one term. The expectation was that SmallVec cap=1 would be faster than Vec, or at worst neutral.

The Assumptions That Were Tested—and Found Wrong

The SmallVec optimization (A1) was proposed based on a reasonable premise: in Filecoin PoRep circuits, most linear combinations in SHA-256 gadgets have 1–3 terms. By using SmallVec<[(usize, Scalar); 4]>, approximately 99% of heap allocations during synthesis could be eliminated. The optimization proposal assumed that eliminating these allocations would reduce memory allocation overhead, improve cache locality by keeping data inline, and reduce pointer-chasing costs.

These assumptions were grounded in conventional wisdom about small-vector optimizations in performance-critical code. SmallVec is a well-known technique in the Rust ecosystem, used in compilers, game engines, and database systems precisely because it avoids heap allocation for small collections. The proposal estimated that each heap allocation costs approximately 15 nanoseconds (allocator overhead plus pointer chase), and that eliminating millions of such allocations would yield a net win.

What the assumptions missed was the specific microarchitecture of the target system: an AMD Zen4 Threadripper PRO 7995WX. On this architecture, jemalloc's thread-local cache is extremely fast—approximately 10–15 nanoseconds per allocation, as the assistant noted in message 995. The heap-allocated Vec data, while not in L1 cache, would likely hit L2 (512 KB per core on Zen3, 1 MB on Zen4) because the thread-local arena stays hot. Moreover, the SmallVec approach increased the struct size of each Indexer from ~24 bytes (Vec: pointer + length + capacity) to ~170 bytes (SmallVec cap=4: inline data + length + discriminant). This meant that 6 Indexers per enforce() call now occupied ~1020 bytes of stack space—16 cache lines—instead of ~144 bytes. The increased stack pressure could cause L1 cache thrashing, especially when combined with the enforce() logic's access to constraint system vectors.

The assistant had intuited this cache-line hypothesis in messages 992–993, proposing that cap=1 would reduce each Indexer to ~56 bytes and the set of 6 to ~336 bytes (~5 cache lines). But the microbenchmark results showed that even cap=1 was 5 seconds slower than Vec. This ruled out the cache-line hypothesis: if the regression were purely about stack size and L1 pressure, cap=1 should have been closer to Vec. The fact that all three SmallVec configurations (cap=1, 2, 4) clustered around 59–60 seconds, while Vec ran at 54.5 seconds, suggested a different mechanism entirely.

Input Knowledge Required to Understand This Message

To fully grasp the significance of message 1025, one needs knowledge spanning several domains:

Groth16 proof generation: The synthesis phase of a Groth16 prover evaluates the circuit's constraints to produce the a/b/c vectors—the core computational work before GPU-based multi-scalar multiplication (MSM) and number-theoretic transform (NTT) operations. In Filecoin's PoRep, this involves evaluating tens of millions of constraints across 10 partitions for a 32 GiB sector.

The cuzk pipeline architecture: The project had built a pipelined proving engine where synthesis (CPU) and GPU proving run concurrently with asynchronous overlap. The SynthesizedProof struct holds the output of bellperson::synthesize_circuits_batch(), including ProvingAssignment<Fr> vectors that are consumed by the GPU phase.

The LC Indexer: In bellpepper-core, the Indexer<T> struct tracks which variables appear in each linear combination during circuit synthesis. It stores Vec<(usize, T)> pairs. The A1 optimization replaced this Vec with SmallVec to avoid heap allocations for the common case of single-term linear combinations.

The AMD Zen4 microarchitecture: The target system's cache hierarchy (32 KB L1d, 1 MB L2, shared L3 per CCD), branch predictor characteristics, and jemalloc performance are all relevant to understanding why SmallVec might not perform as expected.

The optimization proposal framework: The five Wave 1 optimizations (A1, A2, A4, B1, D4) were documented in a detailed proposal document. Each had a rationale, an estimated impact, and a risk assessment. The proposal's estimates were now being empirically validated—and found incorrect.

Output Knowledge Created by This Message

Message 1025 produced several critical pieces of knowledge:

  1. The Vec baseline for synthesis time: 54.5 seconds for a full 10-partition PoRep C2 synthesis. This became the reference point for all subsequent A/B comparisons.
  2. Proof that SmallVec causes a ~5–6 second regression: The difference between 54.5s (Vec) and 59.5–59.9s (SmallVec cap=1) was unambiguous and reproducible across three iterations.
  3. Evidence that the regression is independent of inline capacity: Since cap=1, cap=2, and cap=4 all clustered around 59–60 seconds, the problem was not about cache-line pressure from oversized structs. It was something inherent to SmallVec itself—perhaps the branching overhead of the inline-vs-heap discriminant check, or the cost of moving data between inline storage and heap when a SmallVec grows beyond its inline capacity.
  4. A refined diagnosis target: The assistant now knew to focus on why SmallVec is slower, rather than whether it is slower. This led directly to the next step: gathering perf stat hardware counters (L1/L2/L3 cache misses, branch mispredicts, IPC) on a single-partition run to understand the mechanism.
  5. Validation of the microbenchmark methodology: The synth-only subcommand proved its worth by enabling rapid, reproducible measurements. The three-iteration runs showed tight variance, giving confidence in the results.

The Thinking Process Visible in the Surrounding Messages

The chain of reasoning leading to message 1025 reveals a methodical, hypothesis-driven approach. In message 992, the assistant began by analyzing cache-line alignment: (usize, Scalar) = 40 bytes, SmallVec cap=4 = 160 bytes = 3 cache lines. It hypothesized that cap=1 (40 bytes inline, fitting in one cache line) would be optimal. In message 995, it refined this for AMD Zen3+ characteristics, noting that Vec's heap allocations might actually be fast due to jemalloc's thread-local cache.

The decision to build the synth-only microbenchmark (messages 1000–1019) was itself a recognition that the full E2E test was too slow for iteration. The assistant explored the codebase, identified the synthesis function signature, added the subcommand, and built it—all in under 20 messages. This investment paid off immediately, enabling the four-configuration comparison that definitively identified SmallVec as the regression cause.

After message 1025, the assistant continued testing cap=4 (message 1029: ~60.2s) and cap=2 (message 1030: ~60.0s), confirming the pattern. The next step was to gather perf stat hardware counters to understand why SmallVec was slower—a transition from "what" to "why" that characterizes mature performance engineering.

Mistakes and Incorrect Assumptions

The most significant incorrect assumption was that SmallVec would be faster than Vec on this particular workload and microarchitecture. The optimization proposal had estimated that eliminating heap allocations would save time, but it underestimated two factors:

First, the allocator on this system (jemalloc with thread-local caching) is extremely fast for the small, short-lived allocations typical of synthesis. The 15 ns per allocation estimate may have been reasonable for a general allocator, but on Zen4 with jemalloc's per-thread caches, the actual cost appears to be much lower—perhaps low enough that the SmallVec overhead (branching, discriminant checks, potential moves between inline and heap storage) exceeds the allocation cost.

Second, the proposal may have underestimated the cost of SmallVec's branching logic. Every access to a SmallVec element requires checking whether the data is inline or heap-allocated. In a Vec, the access is a direct pointer dereference with no branch. On a modern CPU with deep pipelines, the mispredicted branch penalty could be significant—especially in a tight loop like the Indexer's values[i] access pattern during constraint evaluation.

A secondary assumption was that the cache-line hypothesis would explain the regression. The assistant initially suspected that cap=4's 160-byte struct was causing L1 cache thrashing. But the cap=1 result (56-byte struct, fitting in one cache line) was equally slow, ruling out this explanation. This is a good example of why microbenchmarks are essential: they prevent over-reliance on plausible-sounding hypotheses.

Broader Significance

Message 1025 represents a critical juncture in the Phase 4 optimization effort. It demonstrated that not all theoretically sound optimizations translate to real-world performance gains, and that measurement—not intuition—must drive engineering decisions. The 5–6 second regression from SmallVec was a humbling result, but it was also a valuable one: it prevented the team from committing a change that would have made the production system slower, and it opened up a deeper investigation into the interaction between data structure choices, allocator behavior, and microarchitecture.

The message also validated the investment in tooling. The synth-only microbenchmark, built in under an hour, enabled the entire diagnostic chain. Without it, the team might have spent days chasing false leads or attributing the regression to other factors. In performance engineering, the quality of your measurement infrastructure determines the quality of your conclusions.

As the session moved forward, the assistant prepared to gather perf stat hardware counters on a single-partition run, aiming to identify the specific microarchitectural mechanism behind the SmallVec regression. Whether the fix would be to abandon SmallVec entirely, to use a different data structure, or to find a way to make SmallVec work on this architecture remained an open question. But message 1025 had established the empirical foundation for answering it.